Convert between various time formats relevant to Chandra.
Chandra.Time provides a simple interface to the C++ time conversion utility axTime3 (which itself is a wrapper for XTime) written by Arnold Rots. Chandra.Time also supports some useful additional time formats.
The supported time formats are:
Format | Description | System |
---|---|---|
secs | Seconds since 1998-01-01T00:00:00 (float) | tt |
numday | DDDD:hh:mm:ss.ss... Elapsed days and time | utc |
relday | [+-]<float> Relative number of days from now | utc |
jd | Julian Day | utc |
mjd | Modified Julian Day = JD - 2400000.5 | utc |
date | YYYY:DDD:hh:mm:ss.ss.. | utc |
caldate | YYYYMonDD at hh:mm:ss.ss.. | utc |
fits | YYYY-MM-DDThh:mm:ss.ss.. | tt |
iso | YYYY-MM-DD hh:mm:ss.ss.. | utc |
unix | Unix time (since 1970.0) | utc |
greta | YYYYDDD.hhmmss[sss] | utc |
year_doy | YYYY:DDD | utc |
mxDateTime | mx.DateTime object | utc |
frac_year | YYYY.ffffff = date as a floating point year | utc |
Each of these formats has an associated time system, which must be one of:
met | Mission Elapsed Time |
tt | Terrestrial Time |
tai | International Atomic Time |
utc | Coordinated Universal Time |
The normal usage is to create an object that allows conversion from one time format to another. Conversion takes place by examining the appropriate attribute. Unless the time format is specified or it is ambiguous (i.e. secs, jd, mjd, and unix), the time format is automatically determined. To specifically select a format use the 'format' option.:
>>> from Chandra.Time import DateTime >>> t = DateTime('1999-07-23T23:56:00') >>> print t.date 1999:204:23:54:55.816 >>> t.date '1999:204:23:54:55.816' >>> t.secs 49161360.0 >>> t.jd 2451383.496479352 >>> DateTime(t.jd + 1, format='jd').fits '1999-07-24T23:56:00.056' >>> DateTime(t.mjd + 1, format='mjd').caldate '1999Jul24 at 23:54:55.820' >>> u = DateTime(1125538824.0, format='unix') >>> u.date '2005:244:01:40:24.000' >>> mxd = mx.DateTime.Parser.DateTimeFromString('1999-01-01 12:13:14') >>> DateTime(mxd).fits '1999-01-01T12:14:18.184' >>> DateTime(mxd).date '1999:001:12:13:14.000' >>> DateTime(mxd).mxDateTime.strftime('%c') 'Fri Jan 1 12:13:14 1999' >>> DateTime('2007122.01020340').date '2007:122:01:02:03.400'
If no input time is supplied when creating the object then the current time is used.:
>>> DateTime().fits '2009-11-14T18:24:14.504'
For convenience a DateTime object can be initialized from another DateTime object.
>>> t = DateTime() >>> u = DateTime(t)
The input time can also be an iterable sequence (returns a list) or a numpy array (returns a numpy array with the same shape):
>>> import numpy >>> DateTime([1,'2001:255',3]).date ['1997:365:23:58:57.816', '2001:255:12:00:00.000', '1997:365:23:58:59.816'] >>> DateTime(numpy.array([[1,2],[3,4]])).fits array([['1998-01-01T00:00:01.000', '1998-01-01T00:00:02.000'], ['1998-01-01T00:00:03.000', '1998-01-01T00:00:04.000']], dtype='|S23')
DateTime objects support a limited arithmetic with a delta time expressed in days. One can add a delta time to a DateTime or subtract a delta time from a DateTime. It is also possible to subtract two DateTiem objects to get a delta time in days. If the DateTime holds a NumPy array or the delta times are NumPy arrays then the appropriate broadcasting will be done.
>>> d1 = DateTime('2011:200:00:00:00') >>> d2 = d1 + 4.25 >>> d2.date '2011:204:06:00:00.000' >>> d2 - d1 4.25 >>> import numpy as np >>> d3 = d1 + np.array([1,2,3]) >>> d3.date array(['2011:201:00:00:00.000', '2011:202:00:00:00.000', '2011:203:00:00:00.000'], dtype='|S21') >>> (d3 + 7).year_doy array(['2011:208', '2011:209', '2011:210'], dtype='|S8')
Currently the object-oriented interface does not allow you to adjust the input or output time system. If you really need to do this, use the package function convert():
>>> import Chandra.Time >>> Chandra.Time.convert(53614.0, ... fmt_in='mjd', ... sys_in='tt', ... fmt_out='caldate', ... sys_out='tai') '2005Aug31 at 23:59:27.816'
The convert() routine will guess fmt_in and supply a default for sys_in if not specified. As for DateTime() the input time can be a sequence or numpy array.